Urbanization trends in China reveal a shift in migration patterns, with an increasing number of recent migrants leaving primate cities while secondary cities emerge as attractive destinations. Given China's aging population and intensifying intercity competition for migrants, understanding the factors associated with recent migrants' intentions to leave cities at various levels becomes increasingly important. While spatial equilibrium theory implies that migrants' leaving intentions are shaped by the balance of housing, employment, and amenities, these factors vary hierarchically across city levels. This study examines how these factors differentially shape recent migrants' leaving intentions across primate, secondary, and small cities. Through binary logistic regression of national survey data, we find that recent migrants in secondary cities exhibit lower leaving intentions compared to those in primate and small cities. Further interaction analyses reveal distinct patterns: in primate cities, medium-income migrants are most likely to consider leaving; in secondary cities, rental housing status and hometown residential land ownership more strongly increase leaving intentions compared to primate cities, while medical resource accessibility more significantly reduces leaving intentions compared to small cities. Drawing on spatial equilibrium theory, our analysis suggests that secondary cities appear to achieve an optimal balance: their greater homeownership opportunities serve as a compensatory factor for their lower incomes compared to primate cities, while their superior medical amenity accessibility compensates for their higher housing costs compared to small cities. This paper contributes theoretically by bridging factors in spatial equilibrium theory with the urban hierarchy dynamics proposed by differential urbanization theory. It also offers practical insights for tailoring migration retention policies across city levels and adapting to the transformation of urbanization stages.

The cooperative behavior of residents is complex and influenced by their complicated social relationships. This complexity is especially noticeable in neighborhood renewal, so the government does not know how to promote residents' cooperative behavior. Therefore, this study proposes an agent-based model (ABM) to investigate the development of residents' cooperative behavior in neighborhood renewal. Based on a questionnaire survey among residents of old neighborhoods in China, the parameters of ABM were determined in this study. Then, controlled experiments were conducted to investigate the effects of general trust among residents and government control of neighborhood renewal on cooperation patterns in renewal projects. In addition, this study examines the effects of different types of social network structures (small-world, scale-free, and random networks) on the evolution of residents' cooperative behaviors. The simulation results show that when residents' initial willingness to agree to renewal projects is high, their close social relationships need to be managed by the government to achieve better outcomes. Conversely, if initial willingness is low, residents' close relationships may pose a challenge to the government. In addition, government-led renewal projects should be encouraged to a greater extent. This study confirms that the different social network structures have an influence on the development of residents' cooperative behavior. The results of this study provide concrete evidence for understanding the factors that contribute to the emergence of residents' cooperative behavior and for studying the effects of government intervention on neighborhood renewal projects. In addition, the results of this study provide theoretical support for future studies of residents' social network structures.